Over the past few months Burtch Works’ entry-level recruiting specialists have been visiting colleges and universities to meet with students who are preparing to enter data analytics jobs. After securing a degree in statistics, mathematics or other related fields, the next challenge for many students is their job search. This will be the first job search for many of them and I wanted to give our specialists an opportunity to share some of their most helpful tips for students.
Burtch Works’ Top Tips for Early Career Analytics Professionals
1. Utilize LinkedIn – Over 90% of corporate and independent recruiters recruit using social media, and the vast majority use LinkedIn. It is fast becoming the go-to resource for companies to check your references and resume, as well as a resource for job seekers to stay updated on company news, search for job postings and develop their network. Having an updated, professional profile on the site allows companies with whom you are applying or interviewing to see you as a person they might want to hire, not just another anonymous resume.
2. Complete an Internship or Project – A great way to test your skills, continue learning and expand your network is to complete an internship. Without previous work experience to go on, prospective employers will look at internships (as well as coursework) to determine if you might be a good fit for their organization. Sometimes – if a company is looking to hire full time and you demonstrate an exceptional work ethic- an internship may also lead to a job offer. If you’re not able to complete an internship, emphasize a data-related hobby or project where you were able to work with lots of real-world data (see below).
3. Get Your Hands On Messy Data – One of the biggest challenges students will face in their first analytics jobs is the lack of experience they have with real-world data sets, so in addition to completing an internship your strategy to enhance your resume must include working with unstructured data. Two great online resources we would recommend are Coursera and Kaggle: Coursera is an online platform where you can take MOOCs (Massive Online Open Curriculum), usually paying a small fee for a certification, and Kaggle hosts data science competitions where you can not only test your abilities against other members, but also get access to large, unstructured data sets more similar to the ones you might use at an analytics job. Completing your SAS certification can also add credibility to your analytic skills, but since many companies are adopting other tools – such as R, Python etc. – you will have a significant advantage if you diversify your skill set.
4. Leverage a Recruiter – Developing a relationship with a recruiter early in your career has many advantages: companies will often have open positions that they fill by working with recruiters (not by posting them on job boards), your resume will be seen by a hiring manager instead of disappearing into a pool of other resumes in their online tracking system, and it lends a more personal experience to what can be a very daunting hiring process. Want to learn more about the interview process, how to get high-quality references and what you can expect at your first job? Check out our webinars on YouTube with tips for early career professionals looking to get into analytics and data science jobs.
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